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<Article>
<Journal>
				<PublisherName>University of Guilan</PublisherName>
				<JournalTitle>Journal of Mathematical Modeling</JournalTitle>
				<Issn>2345-394X</Issn>
				<Volume>5</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2017</Year>
					<Month>06</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>GGMRES: A GMRES--type algorithm for solving singular linear equations with index one</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>1</FirstPage>
			<LastPage>14</LastPage>
			<ELocationID EIdType="pii">1954</ELocationID>
			
<ELocationID EIdType="doi">10.22124/jmm.2017.1954</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Alireza</FirstName>
					<LastName>Ataei</LastName>
<Affiliation>Mathematics Department, Faculty of Science, Persian Gulf University, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Faezeh</FirstName>
					<LastName>Toutounian</LastName>
<Affiliation>Department of Applied Mathematics, School of Mathematical Sciences</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2016</Year>
					<Month>11</Month>
					<Day>25</Day>
				</PubDate>
			</History>
		<Abstract>In this paper, an algorithm based on the Drazin generalized conjugate residual (DGMRES) algorithm is proposed for computing the group-inverse solution of singular linear equations with index one. Numerical experiments show that the resulting group-inverse solution is reasonably accurate and its computation time is significantly less than that of group-inverse solution obtained by the DGMRES algorithm.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">singular linear systems</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">DGMRES method</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">group-inverse solution</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Drazin-inverse solution</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Krylov subspace methods</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jmm.guilan.ac.ir/article_1954_dcd4f79f7ead59a08d2173d1dbddaad0.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>University of Guilan</PublisherName>
				<JournalTitle>Journal of Mathematical Modeling</JournalTitle>
				<Issn>2345-394X</Issn>
				<Volume>5</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2017</Year>
					<Month>06</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Robust portfolio selection with polyhedral ambiguous inputs</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>15</FirstPage>
			<LastPage>26</LastPage>
			<ELocationID EIdType="pii">2004</ELocationID>
			
<ELocationID EIdType="doi">10.22124/jmm.2017.2004</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Somayyeh</FirstName>
					<LastName>Lotfi</LastName>
<Affiliation>Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Maziar</FirstName>
					<LastName>Salahi</LastName>
<Affiliation>Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Farshid</FirstName>
					<LastName>Mehrdoust</LastName>
<Affiliation>Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2016</Year>
					<Month>12</Month>
					<Day>26</Day>
				</PubDate>
			</History>
		<Abstract> Ambiguity in the inputs of the models is typical especially in portfolio selection problem where the true distribution of random variables is usually unknown. Here we use robust optimization approach to address the ambiguity in conditional-value-at-risk minimization model. We obtain explicit models of the robust conditional-value-at-risk minimization for polyhedral and correlated polyhedral ambiguity sets of the scenarios. The models are linear programs in the both cases. Using a portfolio of USA stock market, we apply the buy-and-hold strategy to evaluate the model&#039;s performance. We found that the robust models have almost the same out-of-sample performance, and outperform the nominal model. However, the robust model with correlated polyhedral results in more conservative solutions.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">data ambiguity</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">conditional value-at-risk</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">polyhedral ambiguity set</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">robust optimization</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jmm.guilan.ac.ir/article_2004_1d74d05dba0e222372683aab00dd663c.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>University of Guilan</PublisherName>
				<JournalTitle>Journal of Mathematical Modeling</JournalTitle>
				<Issn>2345-394X</Issn>
				<Volume>5</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2017</Year>
					<Month>06</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>A numerical method for solving nonlinear partial differential equations based on Sinc-Galerkin method</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>27</FirstPage>
			<LastPage>40</LastPage>
			<ELocationID EIdType="pii">2079</ELocationID>
			
<ELocationID EIdType="doi">10.22124/jmm.2017.2079</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Ali</FirstName>
					<LastName>Zakeri</LastName>
<Affiliation>Faculty of Mathematical Sciences, K.N. Toosi University of Technology, P.O. Box 16315-1618, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Amir Hossein</FirstName>
					<LastName>Salehi Shayegan</LastName>
<Affiliation>Faculty of Mathematical Sciences, K.N. Toosi University of Technology, P.O. Box 16315-1618, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Fatemeh</FirstName>
					<LastName>Asadollahi</LastName>
<Affiliation>Faculty of Mathematical Sciences, K.N. Toosi University of Technology, P.O. Box 16315-1618, Tehran, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2017</Year>
					<Month>02</Month>
					<Day>20</Day>
				</PubDate>
			</History>
		<Abstract>In this paper, we consider two dimensional nonlinear elliptic equations of the form $ -{\rm div}(a(u,\nabla u)) = f $. Then, in order to solve these equations on rectangular domains, we propose a numerical method based on Sinc-Galerkin method. Finally, the presented method is tested on some examples. Numerical results show the accuracy and reliability of the proposed method.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Sinc-Galerkin method</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">elliptic partial differential equations</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">nonlinear problems</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">numerical solutions</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jmm.guilan.ac.ir/article_2079_9ed41d4df0353ca9b00dafbb90cd4c8c.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>University of Guilan</PublisherName>
				<JournalTitle>Journal of Mathematical Modeling</JournalTitle>
				<Issn>2345-394X</Issn>
				<Volume>5</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2017</Year>
					<Month>06</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Mixed two-stage derivative estimator for sensitivity analysis</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>41</FirstPage>
			<LastPage>52</LastPage>
			<ELocationID EIdType="pii">2211</ELocationID>
			
<ELocationID EIdType="doi">10.22124/jmm.2017.2211</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Kolsoom</FirstName>
					<LastName>Mirabi</LastName>
<Affiliation>Department of Statistics, School of Mathematical Sciences, Shahrood University of Technology, Shahrood, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mohammad</FirstName>
					<LastName>Arashi</LastName>
<Affiliation>Department of Statistics, School of Mathematical Sciences, Shahrood University of Technology, Shahrood, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2017</Year>
					<Month>05</Month>
					<Day>16</Day>
				</PubDate>
			</History>
		<Abstract>In mathematical modeling, determining most influential parameters on outputs is of major importance. Thus, sensitivity analysis of parameters plays an important role in model validation. We give detailed procedure of constructing a new derivative estimator for general performance measure in Gaussian systems. We will take advantage of using score function and measure-value derivative estimators in our approach. It is shown that the proposed estimator performs better than other estimators for a dense class of test functions in the sense of having smaller variance.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">derivative estimator</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">infinitesimal perturbation analysis</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">measure-valued</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">risk analysis</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">score function</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">stochastic activity network</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jmm.guilan.ac.ir/article_2211_654dd56a77eaa7c5441494a27081eb41.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>University of Guilan</PublisherName>
				<JournalTitle>Journal of Mathematical Modeling</JournalTitle>
				<Issn>2345-394X</Issn>
				<Volume>5</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2017</Year>
					<Month>06</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Determining optimal value of the shape parameter $c$ in RBF for unequal distances topographical points by Cross-Validation algorithm</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>53</FirstPage>
			<LastPage>60</LastPage>
			<ELocationID EIdType="pii">2225</ELocationID>
			
<ELocationID EIdType="doi">10.22124/jmm.2017.2225</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Mohammadreza</FirstName>
					<LastName>Yaghouti</LastName>
<Affiliation>Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Habibe</FirstName>
					<LastName>Ramezannezhad Azarboni</LastName>
<Affiliation>Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2017</Year>
					<Month>05</Month>
					<Day>30</Day>
				</PubDate>
			</History>
		<Abstract>Several radial basis function based methods contain a free shape parameter which has  a crucial role in the accuracy of the methods. Performance evaluation of this parameter in different  functions with various data has always been a topic of study. In the present paper, we consider studying the methods which determine an optimal value for the shape parameter in interpolations of radial basis  functions for data collections produced by topographical images that are not necessarily in equal distances.  The Cross-Validation method is picked out of several existing algorithms proposed for determining the shape parameter.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Radial Basis Function</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Cross-Validation error</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">three-dimensional image</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jmm.guilan.ac.ir/article_2225_aa76072c0b4d04bfa157f4f964478609.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>University of Guilan</PublisherName>
				<JournalTitle>Journal of Mathematical Modeling</JournalTitle>
				<Issn>2345-394X</Issn>
				<Volume>5</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2017</Year>
					<Month>06</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>A numerical approach to solve eighth order boundary value problems by Haar wavelet collocation method</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>61</FirstPage>
			<LastPage>75</LastPage>
			<ELocationID EIdType="pii">2296</ELocationID>
			
<ELocationID EIdType="doi">10.22124/jmm.2017.2296</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Arikera Padmanabha</FirstName>
					<LastName>Reddy</LastName>
<Affiliation>Department of Mathematics, V. S. K. University, Ballari, India</Affiliation>

</Author>
<Author>
					<FirstName>Manjula</FirstName>
					<LastName>Harageri</LastName>
<Affiliation>Department of Mathematics, V. S. K. University, Ballari, India</Affiliation>

</Author>
<Author>
					<FirstName>Channaveerapala</FirstName>
					<LastName>Sateesha</LastName>
<Affiliation>Department of Mathematics, V. S. K. University, Ballari, India</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2017</Year>
					<Month>06</Month>
					<Day>27</Day>
				</PubDate>
			</History>
		<Abstract>In this paper a robust and accurate algorithm based on Haar wavelet collocation method (HWCM) is proposed for solving eighth order boundary value problems. We used the Haar direct method for calculating multiple integrals of Haar functions. To illustrate the efficiency and accuracy of the concerned method, few examples are considered which arise in the mathematical modeling of fluid dynamics and hydromagnetic stability. Convergence and error bound estimation of the method are discussed. The comparison of results with exact solution and existing numerical methods such as Quintic B-spline collocation method and Galerkin method with Quintic B-splines as basis functions shown that the HWCM is a powerful numerical method for solution of above mentioned problems.</Abstract>
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			<Object Type="keyword">
			<Param Name="value">Haar wavelet</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Eighth order boundary value problems</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">collocation method</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jmm.guilan.ac.ir/article_2296_a101cfd2f23c799df5988bdb40444a02.pdf</ArchiveCopySource>
</Article>
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